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Evaluation of diagnostic accuracy of cone beam computed tomography and multi-detector computed tomography for detection of anatomical variations in rhinoplasty

Authors :
Abdolreza Rouientan
Mohammad Bashir Khodaparast
Yaser Safi
Source :
Head & Face Medicine, Vol 20, Iss 1, Pp 1-9 (2024)
Publication Year :
2024
Publisher :
BMC, 2024.

Abstract

Abstract Background Different imaging techniques, such as multi-detector computed tomography (MDCT) scan and cone beam computed tomography(CBCT), are used to check the structure of the nose before rhinoplasty. This study aimed to evaluate the accuracy of two imaging techniques, MDCT scan, and CBCT, in diagnosing structural Variations in rhinoplasty for the first time. Methods This diagnostic accuracy study was conducted on 64 rhinoplasty candidates who complained of snoring and sleep apnea or had a positive result in the examination with Cottleā€™s maneuver or modified Cottle technique between February 2021 and October 2022 at 15- Khordad Hospital affiliated to Beheshti University of Medical Sciences. Before rhinoplasty, patients were randomly assigned to one of the CT and CBCT techniques with an equal ratio. Scans were assessed for the presence of Nasal septum deviation (NSD), Mucocele, Concha bullosa, and nasal septal spur by two independent radiologists. The findings of the two methods were evaluated with the results during rhinoplasty as the gold standard. Results NSD was the most common anatomical variation based on both imaging techniques. The accuracy of CBCT for diagnosing Nasal Septum Deviation and Mucocele was 80% and 75%, respectively. The sensitivity, specificity, and accuracy of CBCT in detecting Concha bullosa were 81.3% and 83.3%, respectively. The Kappa coefficient between CBCT and intraoperative findings for diagnosing NSD and Concha Bullosa was 0.76 and 0.73, respectively (p

Details

Language :
English
ISSN :
1746160X
Volume :
20
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Head & Face Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.689d9d60be0463aa3392c26f5eb6af7
Document Type :
article
Full Text :
https://doi.org/10.1186/s13005-023-00401-1